santaR: Short Asynchronous Time-Series Analysis

A graphical and automated pipeline for the analysis of short time-series in R ('santaR'). This approach is designed to accommodate asynchronous time sampling (i.e. different time points for different individuals), inter-individual variability, noisy measurements and large numbers of variables. Based on a smoothing splines functional model, 'santaR' is able to detect variables highlighting significantly different temporal trajectories between study groups. Designed initially for metabolic phenotyping, 'santaR' is also suited for other Systems Biology disciplines. Command line and graphical analysis (via a 'shiny' application) enable fast and parallel automated analysis and reporting, intuitive visualisation and comprehensive plotting options for non-specialist users.

Version: 1.0
Depends: R (≥ 3.4.0)
Imports: plyr (≥ 1.8.4), foreach (≥ 1.4.4), doParallel (≥ 1.0.11), pcaMethods (≥ 1.70.0), ggplot2 (≥ 2.2.1), gridExtra (≥ 2.3), reshape2 (≥ 1.4.3), iterators (≥ 1.0.9), shiny (≥ 1.0.5), shinythemes (≥ 1.1.1)
Suggests: knitr, rmarkdown, pander, R.rsp
Published: 2018-01-24
Author: Arnaud Wolfer [aut, cre], Timothy Ebbels [ctb], Joe Cheng [ctb] (Shiny javascript custom-input control)
Maintainer: Arnaud Wolfer <adwolfer at>
License: GPL-3
NeedsCompilation: no
Materials: README
CRAN checks: santaR results


Reference manual: santaR.pdf
Vignettes: Advanced command line functions
Automated command line analysis
Getting Started with the santaR package
Plotting options
How to prepare input data for santaR
Selecting an optimal number of degrees of freedom
santaR Theoretical Background
santaR: Graphical user interface
Package source: santaR_1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel: not available
OS X El Capitan binaries: r-release: not available
OS X Mavericks binaries: r-oldrel: not available


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